ORAHS2025
Abstract Submission

140. Constructing a polarity lexicon for depression-specific for sentiment analysis of social media posts

Invited abstract in session HF-5: Innovation 4, stream Sessions.

Thursday, 15:30-17:00
Room: St Olavs, Kunnskapssenteret KA11

Authors (first author is the speaker)

1. Kurt Marais
Logistics, Stellenbosch University

Abstract

Online mental health communities are internet-mediated fora for individuals to share their experiences and challenges, gain understanding through the shared perspective of similar others and to seek advice or support with respect to their own mental health. Mental health information informed in this way also enables individuals without diagnoses to acknowledge the significance of their symptoms and seek professional help. A polarity lexicon for depression consisting of 5718 sentiment-bearing terms was constructed from using posts from the r/depression subreddit to better inform on depression experiences and expressions shared online. A depression-specific lexicon was constructed through a hybrid of traditional and embedding sentiment analysis techniques. The new depression-specific lexicon was evaluated against popular general-purpose lexica that are typically used in the absence of domain-specific corpora. The depression-specific lexicon performed well in the classification of longer social media posts related to depression, whereas the traditional domain-independent VADER lexicon performed marginally better in classifying shorter depression-related posts from Twitter/X. The depression-specific lexicon also improved on the classification of Reddit posts relating to anxiety, loneliness, PTSD and general mental health.

Keywords

Status: accepted

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